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  2. Sign function - Wikipedia

    en.wikipedia.org/wiki/Sign_function

    The signum function of a real number is a piecewise function which is defined as follows: [1] ⁡:= {<, =, > The law of trichotomy states that every real number must be positive, negative or zero. The signum function denotes which unique category a number falls into by mapping it to one of the values −1 , +1 or 0, which can then be used in ...

  3. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    A wide variety of sigmoid functions including the logistic and hyperbolic tangent functions have been used as the activation function of artificial neurons. Sigmoid curves are also common in statistics as cumulative distribution functions (which go from 0 to 1), such as the integrals of the logistic density , the normal density , and Student's ...

  4. Parity of a permutation - Wikipedia

    en.wikipedia.org/wiki/Parity_of_a_permutation

    Parity can be generalized to Coxeter groups: one defines a length function ℓ(v), which depends on a choice of generators (for the symmetric group, adjacent transpositions), and then the function v ↦ (−1) ℓ(v) gives a generalized sign map.

  5. Hard sigmoid - Wikipedia

    en.wikipedia.org/wiki/Hard_sigmoid

    The most extreme examples are the sign function or Heaviside step function, which go from −1 to 1 or 0 to 1 (which to use depends on normalization) at 0. [1]Other examples include the Theano library, which provides two approximations: ultra_fast_sigmoid, which is a multi-part piecewise approximation and hard_sigmoid, which is a 3-part piecewise linear approximation (output 0, line with slope ...

  6. Matrix sign function - Wikipedia

    en.wikipedia.org/wiki/Matrix_sign_function

    The matrix sign function is a generalization of the complex signum function ⁡ = {() >, <, to the matrix valued analogue ⁡ ().Although the sign function is not analytic, the matrix function is well defined for all matrices that have no eigenvalue on the imaginary axis, see for example the Jordan-form-based definition (where the derivatives are all zero).

  7. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

    The activation function of a node in an artificial neural network is a function that calculates the output of the node based on its individual inputs and their weights. Nontrivial problems can be solved using only a few nodes if the activation function is nonlinear .

  8. Zernike polynomials - Wikipedia

    en.wikipedia.org/wiki/Zernike_polynomials

    (even function over the azimuthal angle ... is the sign or signum function. The first 20 fringe numbers are listed below. ... a Python package computing orthogonal ...

  9. Signum function - Wikipedia

    en.wikipedia.org/?title=Signum_function&redirect=no

    Language links are at the top of the page across from the title.